building-threat-intelligence-enrichment-in-splunk

mukul975/Anthropic-Cybersecurity-Skills · updated May 25, 2026

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$npx skills install mukul975/Anthropic-Cybersecurity-Skills/building-threat-intelligence-enrichment-in-splunk
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summary

Build automated threat intelligence enrichment pipelines in Splunk Enterprise Security using lookup tables, modular inputs, and the Threat Intelligence Framework.

skill.md
name
building-threat-intelligence-enrichment-in-splunk
description
Build automated threat intelligence enrichment pipelines in Splunk Enterprise Security using lookup tables, modular inputs, and the Threat Intelligence Framework.
domain
cybersecurity
subdomain
soc-operations
tags
- splunk - threat-intelligence - enrichment - ioc - lookup - siem - soc - enterprise-security
version
'1.0'
author
mahipal
license
Apache-2.0
nist_csf
- DE.CM-01 - DE.AE-02 - RS.MA-01 - DE.AE-06

Building Threat Intelligence Enrichment in Splunk

Overview

Splunk's Threat Intelligence Framework in Enterprise Security enables SOC teams to automatically correlate indicators of compromise (IOCs) against security events. The framework ingests threat feeds, normalizes indicators into KV Store collections, and uses lookup-based correlation searches to flag matching events. Splunk Threat Intelligence Management centralizes collection, normalization, and enrichment from multiple sources, reducing triage time by providing analysts with immediate context.

When to Use

  • When deploying or configuring building threat intelligence enrichment in splunk capabilities in your environment
  • When establishing security controls aligned to compliance requirements
  • When building or improving security architecture for this domain
  • When conducting security assessments that require this implementation

Prerequisites

  • Splunk Enterprise Security (ES) 7.x or later
  • Threat Intelligence Management add-on or Threat Intelligence Framework
  • API keys for external threat intelligence feeds (MISP, OTX, VirusTotal, AbuseIPDB)
  • KV Store enabled and properly configured
  • Admin access for modular input configuration

Threat Intelligence Framework Architecture

External TI Sources (STIX/TAXII, CSV, API)
    |
    v
Modular Inputs (download and parse feeds)
    |
    v
KV Store Collections (normalized IOC storage)
    |-- ip_intel
    |-- domain_intel
    |-- file_intel
    |-- url_intel
    |-- email_intel
    |
    v
Threat Intelligence Lookups
    |
    v
Correlation Searches (match events against IOCs)
    |
    v
Notable Events (enriched with TI context)

Configuring Threat Intelligence Sources

STIX/TAXII Feed Integration

# inputs.conf - TAXII feed configuration
[threatlist://taxii_feed_example]
description = TAXII 2.1 Threat Feed
type = taxii
url = https://threatfeed.example.com/taxii2/
collection = threat-indicators-v21
polling_interval = 3600
api_key = <encrypted_api_key>
disabled = false

CSV-Based Threat List

# inputs.conf - CSV threat list
[threatlist://custom_blocklist]
description = Internal threat blocklist
type = csv
url = https://internal.company.com/threat-feeds/blocklist.csv
polling_interval = 1800
disabled = false

Custom Modular Input for API-Based Feeds

# bin/threatfeed_otx.py - OTX AlienVault feed collector
import json
import sys
import requests
from splunklib.modularinput import Script, Scheme, Argument, Event


class OTXFeedInput(Script):
    def get_scheme(self):
        scheme = Scheme("OTX AlienVault Feed")
        scheme.description = "Collects IOCs from AlienVault OTX"
        scheme.use_external_validation = False
        scheme.streaming_mode = Scheme.streaming_mode_xml

        api_key_arg = Argument("api_key")
        api_key_arg.data_type = Argument.data_type_string
        api_key_arg.required_on_create = True
        scheme.add_argument(api_key_arg)

        pulse_days_arg = Argument("pulse_days")
        pulse_days_arg.data_type = Argument.data_type_number
        pulse_days_arg.required_on_create = False
        scheme.add_argument(pulse_days_arg)

        return scheme

    def stream_events(self, inputs, ew):
        for input_name, input_item in inputs.inputs.items():
            api_key = input_item["api_key"]
            pulse_days = int(input_item.get("pulse_days", 30))

            headers = {"X-OTX-API-KEY": api_key}
            url = f"https://otx.alienvault.com/api/v1/pulses/subscribed?modified_since={pulse_days}d"

            try:
                response = requests.get(url, headers=headers, timeout=60)
                response.raise_for_status()
                data = response.json()

                for pulse in data.get("results", []):
                    for indicator in pulse.get("indicators", []):
                        event = Event()
                        event.stanza = input_name
                        event.data = json.dumps({
                            "indicator": indicator["indicator"],
                            "type": indicator["type"],
                            "pulse_name": pulse["name"],
                            "pulse_id": pulse["id"],
                            "description": indicator.get("description", ""),
                            "created": indicator.get("created", ""),
                            "threat_source": "OTX",
                            "confidence": pulse.get("adversary", "unknown"),
                        })
                        ew.write_event(event)
            except requests.RequestException as e:
                ew.log("ERROR", f"OTX feed collection failed: {str(e)}")


if __name__ == "__main__":
    sys.exit(OTXFeedInput().run(sys.argv))

Building Enrichment Lookups

KV Store Collection Configuration

# collections.conf
[ip_threat_intel]
field.ip = string
field.threat_type = string
field.confidence = number
field.source = string
field.description = string
field.first_seen = time
field.last_seen = time
field.severity = string

[domain_threat_intel]
field.domain = string
field.threat_type = string
field.confidence = number
field.source = string
field.whois_registrar = string
field.whois_created = string

[file_hash_intel]
field.file_hash = string
field.hash_type = string
field.malware_family = string
field.confidence = number
field.source = string
field.detection_names = string

Lookup Table Definitions

# transforms.conf
[ip_threat_intel_lookup]
external_type = kvstore
collection = ip_threat_intel
fields_list = ip, threat_type, confidence, source, description, severity

[domain_threat_intel_lookup]
external_type = kvstore
collection = domain_threat_intel
fields_list = domain, threat_type, confidence, source

[file_hash_intel_lookup]
external_type = kvstore
collection = file_hash_intel
fields_list = file_hash, hash_type, malware_family, confidence, source

Enrichment Correlation Searches

IP-Based Threat Intelligence Correlation

| tstats summariesonly=true count from datamodel=Network_Traffic
    where All_Traffic.action=allowed
    by All_Traffic.src_ip, All_Traffic.dest_ip, All_Traffic.dest_port, _time span=5m
| rename "All_Traffic.*" as *
| lookup ip_threat_intel_lookup ip as dest_ip OUTPUT threat_type, confidence, source as ti_source, severity as ti_severity
| where isnotnull(threat_type)
| lookup asset_lookup ip as src_ip OUTPUT asset_name, asset_owner, asset_priority
| eval urgency=case(
    ti_severity=="critical" AND asset_priority=="critical", "critical",
    ti_severity=="high" OR asset_priority=="critical", "high",
    ti_severity=="medium", "medium",
    true(), "low"
)
| eval description="Connection from ".src_ip." (".asset_name.") to known malicious IP ".dest_ip." (".threat_type.") - Source: ".ti_source

Domain-Based Threat Intelligence Correlation

index=dns sourcetype=stream:dns query_type=A OR query_type=AAAA
| lookup domain_threat_intel_lookup domain as query OUTPUT threat_type as domain_threat, confidence as domain_confidence, source as ti_source
| where isnotnull(domain_threat) AND domain_confidence > 70
| stats count dc(src_ip) as unique_sources values(src_ip) as source_ips by query, domain_threat, ti_source
| eval severity=case(domain_confidence > 90, "critical", domain_confidence > 70, "high", true(), "medium")
| eval description="DNS queries to malicious domain ".query." from ".unique_sources." hosts - Threat: ".domain_threat

File Hash Correlation

index=endpoint sourcetype=sysmon EventCode=1
| lookup file_hash_intel_lookup file_hash as Hashes OUTPUT malware_family, confidence as hash_confidence, source as ti_source
| where isnotnull(malware_family)
| stats count values(ParentCommandLine) as parent_commands by Computer, User, Image, malware_family, ti_source
| eval severity="critical"
| eval description="Known malware ".malware_family." executed on ".Computer." by ".User." - Binary: ".Image

Multi-Source Enrichment Pipeline

index=firewall sourcetype=pan:traffic action=allowed
| eval indicators=mvappend(src_ip, dest_ip)
| mvexpand indicators
| lookup ip_threat_intel_lookup ip as indicators OUTPUT threat_type as ip_threat, confidence as ip_confidence, source as ip_ti_source
| lookup geo_ip_lookup ip as indicators OUTPUT country, city, latitude, longitude
| lookup whois_lookup ip as indicators OUTPUT org as ip_org, asn as ip_asn
| where isnotnull(ip_threat)
| stats count
    values(ip_threat) as threat_types
    values(ip_ti_source) as intel_sources
    values(country) as countries
    values(ip_org) as organizations
    latest(_time) as last_seen
    earliest(_time) as first_seen
    by src_ip, dest_ip, dest_port
| eval enrichment_context="Threat: ".mvjoin(threat_types, ", ")." | Geo: ".mvjoin(countries, ", ")." | Org: ".mvjoin(organizations, ", ")

Threat Intelligence Dashboards

IOC Coverage Statistics

| inputlookup ip_threat_intel_lookup
| stats count by source, threat_type
| sort -count
| head 20

Feed Freshness Monitoring

| inputlookup ip_threat_intel_lookup
| eval age_days=round((now() - strptime(last_seen, "%Y-%m-%dT%H:%M:%S")) / 86400, 0)
| stats count avg(age_days) as avg_age_days max(age_days) as max_age_days by source
| eval status=case(avg_age_days > 30, "STALE", avg_age_days > 7, "AGING", true(), "FRESH")

References

how to use building-threat-intelligence-enrichment-in-splunk

How to use building-threat-intelligence-enrichment-in-splunk on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add building-threat-intelligence-enrichment-in-splunk
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills install mukul975/Anthropic-Cybersecurity-Skills/building-threat-intelligence-enrichment-in-splunk

The skills CLI fetches building-threat-intelligence-enrichment-in-splunk from GitHub repository mukul975/Anthropic-Cybersecurity-Skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/building-threat-intelligence-enrichment-in-splunk

Reload or restart Cursor to activate building-threat-intelligence-enrichment-in-splunk. Access the skill through slash commands (e.g., /building-threat-intelligence-enrichment-in-splunk) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.831 reviews
  • Ganesh Mohane· Dec 24, 2024

    building-threat-intelligence-enrichment-in-splunk has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Dec 20, 2024

    Registry listing for building-threat-intelligence-enrichment-in-splunk matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Kiara Martinez· Dec 16, 2024

    building-threat-intelligence-enrichment-in-splunk is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Zaid Okafor· Dec 12, 2024

    Useful defaults in building-threat-intelligence-enrichment-in-splunk — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Sakshi Patil· Nov 15, 2024

    Solid pick for teams standardizing on skills: building-threat-intelligence-enrichment-in-splunk is focused, and the summary matches what you get after install.

  • Carlos Wang· Nov 7, 2024

    building-threat-intelligence-enrichment-in-splunk reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Maya Haddad· Nov 3, 2024

    I recommend building-threat-intelligence-enrichment-in-splunk for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Carlos Nasser· Oct 26, 2024

    I recommend building-threat-intelligence-enrichment-in-splunk for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Meera Bansal· Oct 22, 2024

    building-threat-intelligence-enrichment-in-splunk reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chaitanya Patil· Oct 6, 2024

    We added building-threat-intelligence-enrichment-in-splunk from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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